Solid State Light (SSL), e.g. Light Emitting Diode (LED), light sources offer significant benefits compared to traditional light sources, e.g. better efficiency, no mercury, instant start, etc. In addition to this, the fast response of these light sources allow to embed some data into the emitted light, such that information is send out and can be retrieved by suitable receivers.
The data to be sent out by the light source has to be stored somewhere, to allow stand-alone operation of the light source. Data may consist of static data, e.g. light source type identifier; one time programmable data, e.g. serial number, and date of installation; and data that changes during operation, e.g. operation hours, and temperature.
In especially for the data that might change during operation, a high effort is required to capture the data, embed it into the data stream and store it into some data storage, which should be non-volatile.
In a normal situation, a lighting device 100 is provided with a relatively competent data generating system, as depicted in FIG. 1, for acquiring data, storing data, and generating data to the lighting device. More particularly, data is transmitted from the data generating system to a light communication part of the lighting device. In particular, the light communication part includes a modulator 110, which is connected with a LED driver 112 and modulates the light output of the lighting device, thereby embedding the data in the light output. The data generating system 100 comprises a non-volatile alterable storage 102, e.g. an EEPROM, a micro processor (μC) 104, sensors 106 sensing external physical effects, and a clock generator 108. Although these are only a few components, in particular the μC will add significant cost to the data generating system. Even problems might result from using a μC, because these devices typically operate at quite high clock speeds in the MHz range, creating EMI emissions.
Looking at the task to be performed by the data generating system, a basic sketch is given in FIG. 2. There are multiple tasks that may be executed in a parallel or serial fashion.
On one hand, measurements have to be taken and translated into digital data. An example might be the actual temperature. In addition, this data might have to be compared to the already stored data, in order to track f.i. the maximum temperature the lighting device has been exposed to, during the total life time. In case the current temperature is higher, the value stored so far has to be replaced by the new value. Operating hours might be tracked, so after the elapse of some time (depending on the granularity), but latest at power down of the lamp, the additional operation hours have to be stored in the memory.
In parallel to this capturing and manipulation of data, a data package has to be prepared for transmission. In the simplest case, the data is stored in the order of the transmission and sent to some modulator. Alternatively, the complete data stream is prepared in a volatile memory, based on input from the non-volatile memory and actual sensing data, and then sent to the modulator.
The prior art data generating system is a complex solution.